Hindawi Publishing Corporation International Journal of Endocrinology Volume 2016, Article ID 1983702, 7 pages http://dx.doi.org/10.1155/2016/1983702
Research Article The Relationship between Alcohol Consumption and Incidence of Glycometabolic Abnormality in Middle-Aged and Elderly Chinese Men Siwen Zhang, Yujia Liu, Gang Wang, Xianchao Xiao, Xiaokun Gang, Fei Li, Chenglin Sun, Ying Gao, and Guixia Wang Department of Endocrinology and Metabolism, The First Hospital of Jilin University, No. 8 Xinmin Street, Changchun, Jilin 130021, China Correspondence should be addressed to Guixia Wang;
[email protected] Received 29 September 2015; Revised 22 December 2015; Accepted 18 January 2016 Academic Editor: Andre P. Kengne Copyright © 2016 Siwen Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Aim. The relationship between alcohol consumption and glycometabolic abnormality is controversial, especially in different ethnic population. In this study, a cross-sectional survey was carried out to examine the relationship between alcohol consumption and glycometabolic abnormality in middle-aged and elderly Chinese men. Methods. Using cluster random sampling, Chinese men aged more than 40 years from Changchun, China, were given standardized questionnaires. In total, 1996 individuals, for whom complete data was available, were recruited into the study. We calculated the incidence of prediabetes and newly diagnosed diabetes by three levels of alcohol consumption: light, moderate, and heavy. Multivariate logistic regression models adjusted for socioeconomic variables and diabetes-related risk factors were used to analyze the association between alcohol consumption and the onset of prediabetes and diabetes. Results. The univariate analysis revealed higher incidence of prediabetes among drinkers (32.8%) compared with nondrinkers (28.6%), particularly in heavy alcohol consumers. The logistic regression analysis showed that alcohol consumption, especially heavy consumption, was an independent risk factor for prediabetes. Conclusions. Alcohol consumption, heavy consumption in particular, is an independent risk factor for the development of prediabetes, but not for diabetes.
1. Introduction Diabetes mellitus is a group of metabolic disorders with phenotypic features similar to those of hyperglycemia. As a chronic condition, diabetes can cause serious complications such as cardiovascular, gastrointestinal, and genitourinary disease and nephropathy, which are major direct causes of diabetes-related deaths [1]. Diabetes has become a major global public health problem and the global burden of diabetes mellitus has been steadily increasing. The onset of type 2 diabetes mellitus (T2DM) is closely associated with diet and lifestyle, especially in people who are prediabetic. Alcohol consumption, a common social custom in most parts of the world, has been reported to be associated with diabetes onset in numerous observational studies [2]. Multiple studies have investigated the association between alcohol consumption and prediabetes and diabetes, and the
results are controversial. A prospective study by Valmadrid et al. indicated that alcohol consumption increases the risk of diabetes [3]. Koppes et al. in a metaregression analysis of 15 prospective studies reported that the relative risk (RR) of T2DM differs with the level of alcohol consumption. Moderate alcohol consumers (6–48 g/day) have a 30% decreased RR of type 2 diabetes compared to nondrinkers [4]. Some epidemiological studies have shown a J- or Ushaped relation between alcohol consumption and T2DM [5]. Although alcohol consumption is common in Chinese culture, people are still unaware of its effects on health. The Chinese National Diabetes Epidemiology Investigation in 2011 revealed that the occurrences of alcohol consumption and diabetes are quite high (38.1%, 6.4%) [6]; therefore, in this study we included participants who were diagnosed with diabetes or prediabetes during the study protocol and excluded those men who have been previously diagnosed
2 with diabetes. We aimed to examine the association between alcohol consumption and glycometabolic abnormality to aid development of prevention strategies and intervention measures for diabetes.
2. Methods The present work is a part of the baseline survey for the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a Longitudinal (REACTION) study, conducted among 259,657 adults, aged ≥40 years from 25 communities across mainland China, from 2011 to 2012 [7–10]. 2.1. Population Selection. Using cluster random sampling via field investigation, we selected residents (dwelling for at least 5 years or more) from 20 communities, including those of Changchun and neighboring communities, who aged more than 40 years. A total of 1996 individuals were successfully recruited into the present study; the response rate was 20.9%. Each participant was provided with an informed consent. The procedures used in this study were approved by the local ethics committee of Jilin University, China, and conformed to the provisions of the Declaration of Helsinki (as revised in Seoul, 2008). 2.2. Exclusion Criteria. Individuals with any of the following conditions were excluded from this study: (1) history of diabetes, (2) recent history of fever, (3) history of cardiovascular disease, (4) acute stress reactions such as infection, surgery, or trauma, and (5) pregnancy. 2.3. Content of Inquiry 2.3.1. Questionnaire Survey. All participants were interviewed by trained physicians or public health workers. Data regarding socioeconomic condition, lifestyle, and health status were collected using standardized questionnaires containing questions on age, sex, race, marital history, reproductive history, level of education, occupation, cigarette smoking, history and treatment of diabetes, physical activity, alcohol consumption-related information including whether currently drinking or not, years of drinking, categories of alcohol beverages (white spirit, beer, claret, and rice wine), and amount of alcohol consumption per day. 2.3.2. Physical Assessments. Blood pressure (BP), pulse, height, weight, waist circumference, and hip circumference were included. BP was measured three times consecutively, with an Omron blood pressure monitor, with an interval of 1 min, and the average of three tests was recorded as the baseline BP. The measurements of height and weight were conducted using Overlord devices. Fasting venous glucose, hepatic function test, renal function test, blood lipid levels, and glycosylated hemoglobin (HbA1C) test of participants are measured. Participants without diabetes were tested with oral glucose tolerance test (OGTT), and for newly diagnosed diabetic subjects, venous glucose concentration was obtained 2 hours after the intake of 100 g of steamed bun. HbA1C was measured
International Journal of Endocrinology with High Performance Liquid Chromatography (HPLC), variant II glycosylated hemoglobin detectors, American Bole Company. 2.4. Diagnostic Criteria. Criteria of glycometabolism categories are as follows [11]: (1) normal glucose regulation (NGR): FBG < 6.1 and 2hPBG < 7.8; (2) prediabetes: I: impaired fasting glucose (IFG): FBG: 6.1–7.0 and 2hPBG < 7.8; II: impaired glucose tolerance (IGT): FBG < 7.0 and 2hPBG: 7.8–11.1; and (3) DM: FBG ≥ 7.0 or 2hPBG ≥ 11.1 (FBG: Fasting Blood Glucose, mmol/L; 2hPBG: 2-Hour Postprandial Blood Glucose, mmol/L). According to the criteria of 2010 Chinese guidelines for the management of hypertension, hypertension can be diagnosed based on at least one of the following items: (1) systolic pressure (SP) ≥ 140 mmHg; (2) diastolic pressure (DP) ≥ 90 mmHg; and (3) previous hypertension. According to the recommendations of the Working Group on Obesity in China, 2002, (1) overweight is 24.0 kg/m2 ≤ body mass index (BMI) < 28.0 kg/m2 and (2) obesity is BMI ≥ 28.0 kg/m2 . 2.5. Definition of Relative Risk Factors. Alcohol consumption assessment is as follows: (1) nondrinker: never consumed or consumed alcohol occasionally; (2) drinker: consumed alcohol (any type) at least once a week; (1) light alcohol consumption: amount < 30 g/d; (2) moderate alcohol consumption: 30 g/d ≤ amount < 50 g/d; and (3) heavy alcohol consumption: amount ≥ 50 g/d (amount [g/d] = daily alcohol volume [mL] ∗ alcoholicity [V/V] ∗ density [g/mL]; density of alcohol was calculated as 0.8 g/mL) [12]. 2.6. Cigarette Smoking Assessment. Participants who smoked at least one cigarette per day or seven cigarettes per week for more than 6 months were defined as “smokers.” Individuals who had never smoked or smoked occasionally were defined as “nonsmokers.” 2.7. Statistical Methods. Results of questionnaire and laboratory testing were fed into EXCEL to set up a database to be used for data analysis. Descriptive and comparable statistical analyses between “drinker” and “nondrinker” groups with the parameters age, BMI, waist-hip ratio (WHR), hepatic function, renal function, FBG, 2hPBG, and HbA1C were conducted. Statistics were generated with SPSS (version 18.0, SPSS Inc., IBM, Armonk, NY, USA). Measurement data were expressed as mean ± SD. Disease risk was evaluated as odds ratio (OR). Univariate analysis was conducted with chisquare test. The average levels of two groups were measured with 𝑡-test. Multivariate logistic regression models adjusted for confounding factors were used to examine ordinal variable.
3. Results The basic information of participants is that a total of 1996 men aged more than 40 years were examined. Baseline demographic and other characteristics of the study participants are presented in Table 1. The mean age of the participants
International Journal of Endocrinology
40
3 ∗
∗
40
30 Incidences (%)
Incidences (%)
30
20
20
10
10
0
0 Prediabetes
Prediabetes
Diabetes
Diabetes
Nondrinkers Light consumption
Nondrinkers Drinkers (a)
Moderate consumption Heavy consumption
(b)
Figure 1: (a) The incidence of prediabetes and diabetes in group of drinkers and nondrinkers. 28.6% and 32.8% of drinkers showed prediabetes and diabetes; 13.6% and 16.5% of nondrinkers showed prediabetes and diabetes. (b) The incidence rates of prediabetes and diabetes in the case of none, light, moderate, and heavy alcohol consumption. Table 1: Baseline demographics and characteristics of participants. Participants, 𝑛 (%) Age∗ , y BMI, kg/m2 WHR FPG (mmol/L) 2hPG (mmol/L) HbA1c (%) SBP∗ (mmHg) DBP∗ (mmHg) ALT∗ (U/L) AST∗ (U/L) GGT∗ (U/L) Family history of diabetes, 𝑛 (%) Education∗ >11 years, 𝑛 (%) Smoking status∗ (%) Regular physical activity∗ , 𝑛, % High energy intake, 𝑛 (%) ∗
Nondrinkers 1358 (68.03%) 58.24 ± 11.0 25.37 ± 3.29 0.88 ± 0.06 5.87 ± 1.37 7.57 ± 3.34 5.85 ± 0.79 141.84 ± 21.20 82.72 ± 11.72 16.03 ± 11.37 22.27 ± 9.19 34.82 ± 33.21 131 (9.92%) 863 (63.55%) 416 (31.42%) 928 (68.34%) 513 (37.78%)
Drinkers 638 (31.96%) 56.54 ± 9.70 25.54 ± 3.68 0.89 ± 0.06 5.98 ± 1.38 7.78 ± 3.48 5.85 ± 0.85 144.25 ± 20.25 84.88 ± 11.47 17.30 ± 11.77 25.42 ± 17.32 61.97 ± 91.08 57 (9.36%) 370 (57.99%) 435 (71.55%) 392 (61.44%) 246 (38.56%)
𝑃 0.015 0.121 0.182 0.097 0.182 0.951 0.011
